Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies.

Learn to apply multiple regression techniques to predict continuous outcomes, use logistic regression for binary outcomes, and employ Cox regression for survival analysis.

Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff, Tor D. Wager, Lisa Feldman Barrett, Shir Atzil, Timothy D. Johnson, Thomas E. Nichols, Bayesian log-Gaussian Cox process regression, ...

This article investigates an augmented inverse selection probability weighted estimator for Cox regression parameter estimation when covariate variables are incomplete. This estimator extends the ...

Univariate Cox regression models were used to assess the relationship between continuous expression levels of ARGs and overall survival (OS) to assess the prognostic significance of each gene, and ...

Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...